The assignment of direction and causality within networks of observational associations is problematic outside randomized control trials and the presence of causal a relationship between body mass index (BMI) and C-reactive protein (CRP) is disputed.

Objective

Using reciprocal Mendelian randomization, we aim to assess the direction of causality in relationships between BMI and CRP and to demonstrate this as a promising analytical technique.

Participants and methods

The Study was based in a large, cross-sectional European study from Copenhagen, Denmark. Genetic associates of BMI (FTOrs9939609) and circulating CRP (CRPrs3091244) have been used to re-examine observational associations between them.

Results

Observational analyses showed strong, positive association between circulating CRP and BMI (change in BMI for a doubling in logCRP of 1.03kg/m2 (95%CI 1.00, 1.07), p<0.0001). Analysis using CRPrs3091244 to re-estimate the causal effect of circulating CRP on BMI yielded null effects (change in BMI for a doubling in logCRP of −0.24kg/m2 (95%CI −0.58, 0.11), p=0.2). In contrast, analysis using FTOrs9939609 to assess the causal effect of BMI on circulating CRP confirmed observational associations (ratio of geometric means of CRP per standard deviation increase in BMI 1.41(95%CI 1.10, 1.80), p=0.006).

Conclusions

Together, these data suggest that the observed association between circulating CRP and measured BMI is likely to be driven by BMI, with CRP being a marker of elevated adiposity. More generally, the method of reciprocal randomization has general applicability in determining direction of causation within inter-correlated networks of metabolic components and methods such as this provide an approach for delivering immediate and clinically applicable information.

L-ascorbic acid is an essential part of the human diet and has been associated with a wide-range of chronic complex diseases including cardiovascular outcomes. To date, there are no confirmed genetic correlates of circulating levels of L-ascorbic acid.

Objectives

We aimed to confirm the existence of association between common variation at the SLC23A1 gene locus and circulating levels of L-ascorbic acid.

Design

We employed a two-stage design which used a discovery cohort (the British Women’s Heart and Health Study) and a series of follow-up cohorts and meta-analysis (totalling 15087 participants) to assess the relationship between variation at SLC23A1 and circulating levels of L-ascorbic acid.

Results

In the discovery cohort, variation at rs33972313 was associated with a reduction in circulating levels of L-ascorbic acid (−4.15μmol/L (95%CI −0.49, −7.81), p=0.03 reduction per minor allele). Pooled analysis of the relationship between rs33972313 and circulating L-ascorbic acid across all studies confirmed this, showing that each additional rare allele was associated with a reduction in circulating levels of L-ascorbic acid of −5.98μmol/L (95%CI −8.23, −3.73), p=2.0×10−7 per minor allele.

Conclusion

Work here has identified a genetic variant (rs33972313) in the SLC23A1 vitamin C active transporter locus that is reliably associated with circulating levels of L-ascorbic acid in the general population. This finding has implications more generally for the epidemiological investigation of relationships between circulating L-ascorbic acid and health outcomes.

Identification of causes of dementia soon after symptom onset is important, because appropriate treatment of some causes of dementia can slow or halt its progression or enable symptomatic treatment where appropriate. The accuracy of MRI and CT, and whether MRI is superior to CT, in detecting a vascular component to dementia in autopsy confirmed and clinical cohorts of patients with VaD, combined AD and VaD (“mixed dementia”), and AD remain unclear. We conducted a systematic review and meta-analysis to investigate this question.

Methods

We searched eight databases and screened reference lists to identify studies addressing the review question. We assessed study quality using QUADAS. We estimated summary diagnostic accuracy according to imaging finding, and ratios of diagnostic odds ratios (RDORs) for MRI versus CT and high versus low risk of bias.

Results

We included 7 autopsy and 31 non-autopsy studies. There was little evidence that selective patient enrolment and risk of incorporation bias impacted on diagnostic accuracy (p = 0.12 to 0.95). The most widely reported imaging finding was white matter hyperintensities. For CT (11 studies) summary sensitivity and specificity were 71% (95% CI 53%-85%) and 55% (44%-66%). Corresponding figures for MRI (6 studies) were 95% (87%-98%) and 26% (12%-50%). General infarcts was the most specific imaging finding on MRI (96%; 95% CI 94%-97%) and CT (96%; 93%-98%). However, sensitivity was low for both MRI (53%; 36%-70%) and CT (52%; 22% to 80%). No imaging finding had consistently high sensitivity. Based on non-autopsy studies, MRI was more accurate than CT for six of seven imaging findings, but confidence intervals were wide.

Conclusion

There is insufficient evidence to suggest that MRI is superior to CT with respect to identifying cerebrovascular changes in autopsy-confirmed and clinical cohorts of VaD, AD, and ‘mixed dementia’.

The causal nature of associations between circulating triglycerides, insulin resistance, and type 2 diabetes is unclear. We aimed to use Mendelian randomization to test the hypothesis that raised circulating triglyceride levels causally influence the risk of type 2 diabetes and raise normal fasting glucose levels and hepatic insulin resistance.

RESEARCH DESIGN AND METHODS

We tested 10 common genetic variants robustly associated with circulating triglyceride levels against the type 2 diabetes status in 5,637 case and 6,860 control subjects and four continuous outcomes (reflecting glycemia and hepatic insulin resistance) in 8,271 nondiabetic individuals from four studies.

Genetically raised circulating triglyceride levels do not increase the risk of type 2 diabetes or raise fasting glucose or fasting insulin levels in nondiabetic individuals. One explanation for our results is that raised circulating triglycerides are predominantly secondary to the diabetes disease process rather than causal.

Genetically raised circulating triglyceride levels do not increase the risk of type 2 diabetes, or raise fasting glucose or fasting insulin levels in non-diabetic individuals. One explanation for our results is that raised circulating triglycerides are predominantly secondary to the diabetes disease process rather than causal.

It is unclear whether C-reactive protein (CRP) is causally related to coronary heart disease (CHD). Genetic variants that are known to be associated with CRP levels can be used to provide causal inference of the effect of CRP on CHD. Our objective was to examine the association between CRP genetic variant +1444C>T (rs1130864) and CHD risk in the largest study to date of this association.

Methods and Results

We estimated the association of CRP genetic variant +1444C>T (rs1130864) with CRP levels and with CHD in five studies and then pooled these analyses (N = 18,637 participants amongst whom there were 4,610 cases). CRP was associated with potential confounding factors (socioeconomic position, physical activity, smoking and body mass) whereas genotype (rs1130864) was not associated with these confounders. The pooled odds ratio of CHD per doubling of circulating CRP level after adjustment for age and sex was 1.13 (95%CI: 1.06, 1.21), and after further adjustment for confounding factors it was 1.07 (95%CI: 1.02, 1.13). Genotype (rs1130864) was associated with circulating CRP; the pooled ratio of geometric means of CRP level among individuals with the TT genotype compared to those with the CT/CC genotype was 1.21 (95%CI: 1.15, 1.28) and the pooled ratio of geometric means of CRP level per additional T allele was 1.14 (95%CI: 1.11, 1.18), with no strong evidence in either analyses of between study heterogeneity (I2 = 0%, p>0.9 for both analyses). There was no association of genotype (rs1130864) with CHD: pooled odds ratio 1.01 (95%CI: 0.88, 1.16) comparing individuals with TT genotype to those with CT/CC genotype and 0.96 (95%CI: 0.90, 1.03) per additional T allele (I2<7.5%, p>0.6 for both meta-analyses). An instrumental variables analysis (in which the proportion of CRP levels explained by rs1130864 was related to CHD) suggested that circulating CRP was not associated with CHD: the odds ratio for a doubling of CRP level was 1.04 (95%CI: 0.61, 1.80).

Conclusions

We found no association of a genetic variant, which is known to be related to CRP levels, (rs1130864) and having CHD. These findings do not support a causal association between circulating CRP and CHD risk, but very large, extended, genetic association studies would be required to rule this out.

Alcohol has been reported to be a common and modifiable risk factor for hypertension. However, observational studies are subject to confounding by other behavioural and sociodemographic factors, while clinical trials are difficult to implement and have limited follow-up time. Mendelian randomization can provide robust evidence on the nature of this association by use of a common polymorphism in aldehyde dehydrogenase 2 (ALDH2) as a surrogate for measuring alcohol consumption. ALDH2 encodes a major enzyme involved in alcohol metabolism. Individuals homozygous for the null variant (*2*2) experience adverse symptoms when drinking alcohol and consequently drink considerably less alcohol than wild-type homozygotes (*1*1) or heterozygotes. We hypothesise that this polymorphism may influence the risk of hypertension by affecting alcohol drinking behaviour.

These findings support the hypothesis that alcohol intake has a marked effect on blood pressure and the risk of hypertension.

Using a mendelian randomization approach Sarah Lewis and colleagues find strong support for the hypothesis that alcohol intake has a marked effect on blood pressure and the risk of hypertension.

Editors' Summary

Background.

High blood pressure (hypertension) is a common medical condition that affects nearly a third of US and UK adults. Hypertension has no symptoms but can lead to heart attacks or strokes. It is diagnosed by measuring blood pressure—the force that blood moving around the body exerts on the inside of large blood vessels. Blood pressure is highest when the heart is pumping out blood (systolic pressure) and lowest when it is filling up with blood (diastolic pressure). Normal blood pressure is defined as a systolic pressure of less than 130 millimeters of mercury (mmHg) and a diastolic pressure of less than 85 mmHg (a blood pressure of 130/85). A reading of more than 140/90 indicates hypertension. Many factors affect blood pressure, but overweight people and individuals who eat too much salty or fatty foods are at high risk of developing hypertension. Mild hypertension can often be corrected by lifestyle changes, but many people also take antihypertensive drugs to reduce their blood pressure.

Why Was This Study Done?

Another modifiable lifestyle factor thought to affect blood pressure is alcohol intake. Observational studies that ask people about their drinking habits and measure their blood pressure suggest that alcohol intake correlates with blood pressure, but they cannot prove a causal link because of “confounding”—other risk factors associated with alcohol drinking, such as diet, might also affect the study participant's blood pressures. A trial that randomly assigns people to different alcohol intakes could provide this proof of causality, but such a trial is impractical. In this study, therefore, the researchers have used “Mendelian randomization” to investigate whether alcohol intake affects blood pressure. An inactive variant of aldehyde dehydrogenase 2 (ALDH2; the enzyme that removes alcohol from the body) has been identified. People who inherit the variant form of this gene from both parents have an ALDH2 *2*2 genotype (genetic makeup) and become flushed and nauseated after drinking. Consequently, they drink less than people with a *1*2 genotype and much less than those with a *1*1 genotype. Because inheritance of these genetic variants does not affect lifestyle factors other than alcohol intake, an association between ALDH2 genotypes and blood pressure would indicate that alcohol intake has an effect on blood pressure without any confounding.

What Did the Researchers Do and Find?

The researchers identified ten published studies (mainly done in Japan where the ALDH2 gene variant is common) on associations between ALDH2 genotype and blood pressure or hypertension using a detailed search protocol (a “systematic review”). A meta-analysis (a statistical method for combining the results of independent studies) of the studies that had investigated the association between ALDH2 genotype and hypertension showed that men with the *1*1 genotype (highest alcohol intake) and those with the *1*2 genotype (intermediate alcohol intake) were 2.42 and 1.72 times more likely, respectively, to have hypertension than those with the *2*2 genotype (lowest alcohol intake). There was no association between ALDH2 genotype and hypertension among the women in these studies because they drank very little. Systolic and diastolic blood pressures showed a similar relationship to ALDH2 genotype in a second meta-analysis of relevant studies. Finally, the researchers estimated that for men the lifetime effect of drinking 1 g of alcohol a day (one unit of alcohol contains 8 g of alcohol in the UK and 14 g in the US; recommended daily limits in these countries are 3–4 and 1–2 units, respectively) would be an increase in systolic blood pressure of 0.24 mmHg.

What Do These Findings Mean?

These findings support the suggestion that alcohol has a marked effect on blood pressure and hypertension. Consequently, some cases of hypertension could be prevented by encouraging people to reduce their daily alcohol intake. Although the Mendelian randomization approach avoids most of the confounding intrinsic to observational studies, it is possible that a gene near ALDH2 that has no effect on alcohol intake affects blood pressure, since genes are often inherited in blocks. Alternatively, ALDH2 could affect blood pressure independent of alcohol intake. The possibility that ALDH2 could effect blood pressure independently of alcohol is intake made unlikely by the fact that no effect of genotype on blood pressure is seen among women who drink very little. Additional large-scale studies are needed to address these possibilities, to confirm the current finding in more people, and to improve the estimates of the effect that alcohol intake has on blood pressure.

Additional Information.

Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050052.

The MedlinePlus encyclopedia has a page on hypertension (in English and Spanish)

The American Heart Association provides information for patients and health professionals about hypertension

The UK Blood Pressure Association provides information for patients and health professionals on all aspects of hypertension, including information about alcohol affects blood pressure

The Explore@Bristol science center (a UK charity) provides an alcohol unit calculator and information on the effects of alcohol

The International Center for Alcohol Policies provides drinking guidelines for countries around the world

The developmental overnutrition hypothesis suggests that greater maternal obesity during pregnancy results in increased offspring adiposity in later life. If true, this would result in the obesity epidemic progressing across generations irrespective of environmental or genetic changes. It is therefore important to robustly test this hypothesis.

Methods and Findings

We explored this hypothesis by comparing the associations of maternal and paternal pre-pregnancy body mass index (BMI) with offspring dual energy X-ray absorptiometry (DXA)–determined fat mass measured at 9 to 11 y (4,091 parent–offspring trios) and by using maternal FTO genotype, controlling for offspring FTO genotype, as an instrument for maternal adiposity. Both maternal and paternal BMI were positively associated with offspring fat mass, but the maternal association effect size was larger than that in the paternal association in all models: mean difference in offspring sex- and age-standardised fat mass z-score per 1 standard deviation BMI 0.24 (95% confidence interval [CI]: 0.22 to 0.26) for maternal BMI versus 0.13 (95% CI: 0.11, 0.15) for paternal BMI; p-value for difference in effect < 0.001. The stronger maternal association was robust to sensitivity analyses assuming levels of non-paternity up to 20%. When maternal FTO, controlling for offspring FTO, was used as an instrument for the effect of maternal adiposity, the mean difference in offspring fat mass z-score per 1 standard deviation maternal BMI was −0.08 (95% CI: −0.56 to 0.41), with no strong statistical evidence that this differed from the observational ordinary least squares analyses (p = 0.17).

Conclusions

Neither our parental comparisons nor the use of FTO genotype as an instrumental variable, suggest that greater maternal BMI during offspring development has a marked effect on offspring fat mass at age 9–11 y. Developmental overnutrition related to greater maternal BMI is unlikely to have driven the recent obesity epidemic.

Using parental-offspring associations and theFTO gene as an instrumental variable for maternal adiposity, Debbie Lawlor and colleagues found that greater maternal BMI during offspring development does not appear to have a marked effect on offspring fat mass at age 9-11.

Editors' Summary

Background.

Since the 1970s, the proportion of children and adults who are overweight or obese (people who have an unhealthy amount of body fat) has increased sharply in many countries. In the US, 1 in 3 adults is now obese; in the mid-1970s it was only 1 in 7. Similarly, the proportion of overweight children has risen from 1 in 20 to 1 in 5. An adult is considered to be overweight if their body mass index (BMI)—their weight in kilograms divided by their height in meters squared—is between 25 and 30, and obese if it is more than 30. For children, the healthy BMI depends on their age and gender. Compared to people with a healthy weight (a BMI between 18.5 and 25), overweight or obese individuals have an increased lifetime risk of developing diabetes and other adverse health conditions, sometimes becoming ill while they are still young. People become unhealthily fat when they consume food and drink that contains more energy than they need for their daily activities. It should, therefore, be possible to avoid becoming obese by having a healthy diet and exercising regularly.

Why Was This Study Done?

Some researchers think that “developmental overnutrition” may have caused the recent increase in waistline measurements. In other words, if a mother is overweight during pregnancy, high sugar and fat levels in her body might permanently affect her growing baby's appetite control and metabolism, and so her offspring might be at risk of becoming obese in later life. If this hypothesis is true, each generation will tend to be fatter than the previous one and it will be very hard to halt the obesity epidemic simply by encouraging people to eat less and exercise more. In this study, the researchers have used two approaches to test the developmental overnutrition hypothesis. First, they have asked whether offspring fat mass is more strongly related to maternal BMI than to paternal BMI; it should be if the hypothesis is true. Second, they have asked whether a genetic indicator of maternal fatness—the “A” variant of the FTO gene—is related to offspring fat mass. A statistical association between maternal FTO genotype (genetic make-up) and offspring fat mass would support the developmental nutrition hypothesis.

What Did the Researchers Do and Find?

In 1991–1992, the Avon Longitudinal Study of Parents and Children (ALSPAC) enrolled about 14,000 pregnant women and now examines their offspring at regular intervals. The researchers first used statistical methods to look for associations between the self-reported prepregnancy BMI of the parents of about 4,000 children and the children's fat mass at ages 9–11 years measured using a technique called dual energy X-ray absorptiometry. Both maternal and paternal BMI were positively associated with offspring fat mass (that is, fatter parents had fatter children) but the effect of maternal BMI was greater than the effect of paternal BMI. When the researchers examined maternal FTO genotypes and offspring fat mass (after allowing for the offspring's FTO genotype, which would directly affect their fat mass), there was no statistical evidence to suggest that differences in offspring fat mass were related to the maternal FTO genotype.

What Do These Findings Mean?

Although the findings from first approach provide some support for the development overnutrition hypothesis, the effect of maternal BMI on offspring fat mass is too weak to explain the recent obesity epidemic. Developmental overnutrition could, however, be responsible for the much slower increase in obesity that began a century ago. The findings from the second approach provide no support for the developmental overnutrition hypothesis, although these results have wide error margins and need confirming in a larger study. The researchers also note that the effects of developmental overnutrition on offspring fat mass, although weak at age 9–11, might become more important at later ages. Nevertheless, for now, it seems unlikely that developmental overnutrition has been a major driver of the recent obesity epidemic. Interventions that aim to improve people's diet and to increase their physical activity levels could therefore slow or even halt the epidemic.

Additional Information.

Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050033.

See a related PLoS Medicine Perspective article

The MedlinePlus encyclopedia has a page on obesity (in English and Spanish)

The US Centers for Disease Control and Prevention provides information on all aspects of obesity (in English and Spanish)

Mendelian randomisation analyses use genetic variants as instrumental variables (IVs) to estimate causal effects of modifiable risk factors on disease outcomes. Genetic variants typically explain a small proportion of the variability in risk factors; hence Mendelian randomisation analyses can require large sample sizes. However, an increasing number of genetic variants have been found to be robustly associated with disease-related outcomes in genome-wide association studies. Use of multiple instruments can improve the precision of IV estimates, and also permit examination of underlying IV assumptions. We discuss the use of multiple genetic variants in Mendelian randomisation analyses with continuous outcome variables where all relationships are assumed to be linear. We describe possible violations of IV assumptions, and how multiple instrument analyses can be used to identify them. We present an example using four adiposity-associated genetic variants as IVs for the causal effect of fat mass on bone density, using data on 5509 children enrolled in the ALSPAC birth cohort study. We also use simulation studies to examine the effect of different sets of IVs on precision and bias. When each instrument independently explains variability in the risk factor, use of multiple instruments increases the precision of IV estimates. However, inclusion of weak instruments could increase finite sample bias. Missing data on multiple genetic variants can diminish the available sample size, compared with single instrument analyses. In simulations with additive genotype-risk factor effects, IV estimates using a weighted allele score had similar properties to estimates using multiple instruments. Under the correct conditions, multiple instrument analyses are a promising approach for Mendelian randomisation studies. Further research is required into multiple imputation methods to address missing data issues in IV estimation.